The aim of the proposed small grant project is to examine change in functional status of the elderly and factors/covariates predicting such change, using an existing national independently is an important determinant of health and well-being in older adults, studying change in functional status and accompanying factors is both substantively and practically important in terms of understanding aging processes and designing interventions for reduction of the morbidity and extension of the productivity, independence, and well-being of older adults. In this proposal, new analytical techniques suited to the longitudinal data structure and research objectives will be employed. These include hierarchical linear modeling and latent growth curve modeling methodologies. The methodologies involved avoid many of the limitations associated with more traditional longitudinal data analytic strategies. Developmental models reflecting univariate and multivariate longitudinal change patterns in functional status will be specified and tested. Additionally, influences of physical, psychological, social, and demographic variables on change will be examined as risk and protective factors that either enhance or undermine functional status. A great deal of time and money has been expended to obtain excellent data sets, but the data have not been analyzed using state-of the-art analytic techniques specifically designed for hierarchical and multilevel longitudinal data. The longitudinal nature of the data to be examined will allow us to construct, estimate, and test a variety of complex growth models concerning changes in health and functional capacity of older adults. The combination of a relatively large national sample of older adults and contemporary methods for the analysis of longitudinal change in self-maintaining functions and predictors and correlates of the change will allow us to explore patterns of relationships in older adults that might otherwise go unexplored in the data set. Furthermore, examination of change in functional status within a multivariate longitudinal framework is likely to further enhance our understanding of aging processes in terms of levels of functioning among the elderly and help to develop means to maintain quality of life and autonomy with aging individuals.